Image Processing for Rounded Screens Using Quadrant Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing methods for rectangular images on devices with rounded screens require extensive calculations, leading to significant GPU consumption and performance degradation, as they need to match the image's right angles with the rounded screen through rounded-corner processing.
Innovation Solution
The method divides the image into areas based on right angles, establishing a rectangular coordinate system for each area, determining if a pixel is within the first quadrant, and performing operations only on pixels in this quadrant, thereby reducing unnecessary calculations and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Shape
If rounded-corner processing is performed on each pixel in the image, then the image shape matches the rounded screen, but the calculation amount increases significantly and GPU consumption increases
Solution Approach 1:
The image is divided into multiple regions based on the rounded corner areas. Only pixels within these specific regions undergo rounded-corner processing, while other pixels are handled differently. This segmentation reduces the number of pixels requiring complex calculations, thereby lowering GPU consumption while still achieving proper shape matching for the rounded screen display.
2Shape
If rounded-corner processing is performed on each pixel in the image, then the image shape matches the rounded screen, but the processing time increases
Solution Approach 1:
The image is divided into multiple regions based on the rounded corner areas. Only pixels within these specific regions undergo rounded-corner processing, while other pixels are handled differently. This segmentation reduces the number of pixels requiring complex calculations, thereby lowering GPU consumption while still achieving proper shape matching for the rounded screen display.
3Manufacturing precision
If operations are performed on all pixels to determine rounded-corner status, then accurate rounded-corner processing is achieved, but device performance is affected
Solution Approach 1:
The image is divided into multiple regions based on the rounded corner areas. Only pixels within these specific regions undergo rounded-corner processing, while other pixels are handled differently. This segmentation reduces the number of pixels requiring complex calculations, thereby lowering GPU consumption while still achieving proper shape matching for the rounded screen display.
Solution Approach 2:
Different processing methods are applied to different regions of the image. Pixels within the rounded corner regions undergo specific rounded-corner processing to ensure accuracy, while pixels in other regions use alternative methods. This local quality approach maintains processing accuracy where needed while improving overall device performance.
Data Source
AI summary
Aspects of this disclosure can provide a method that is applied to an image with a rectangular shape. The method can include dividing the image into a plurality of areas based on right angles of the image, and establishing a corresponding rectangular coordinate system for the right angle within each of the plurality of areas. Further, an intersection of a first axis and a second axis is taken as an origin of the rectangular coordinate system and a quadrant where the right angle is located is taken as a first quadrant of the corresponding rectangular coordinate system. The method can further include determining whether a pixel in the image is located in the first quadrant, and, if it is determined that the pixel is located in the first quadrant of the rectangular coordinate system, performing an operation on the pixel, otherwise, performing no operation on the pixel.